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Advisor(s)
Abstract(s)
Nearshore bathymetry is likely to be the coastal variable that most limits the investigation of coastal processes
and the accuracy of numerical models in coastal areas, as acquiring medium spatial resolution data in the nearshore
is highly demanding and costly. As such, the ability to derive bathymetry using remote sensing techniques
is a topic of increasing interest in coastalmonitoring and research. This contribution focuses on the application of
the linear transform algorithm to obtain satellite-derived bathymetry (SDB) maps of the nearshore, at medium
resolution (30 m), from freely available and easily accessible Landsat 8 imagery. The algorithm was tuned with
available bathymetric Light Detection and Ranging (LiDAR) data for a 60-km-long nearshore stretch of a highly
complex coastal system that includes barrier islands, exposed sandy beaches, and tidal inlets (Ria Formosa,
Portugal). A comparison of the retrieved depths is presented, enabling the configuration of nearshore profiles
and extracted isobaths to be explored and compared with traditional topographic/bathymetric techniques
(e.g., high- and medium-resolution LiDAR data and survey-grade echo-sounding combined with high-precision
positioning systems). The results demonstrate that the linear algorithm is efficient for retrieving bathymetry
frommulti-spectral satellite data for shallowwater depths (0 to 12 m), showing amean bias of−0.2m, a median
difference of −0.1 m, and a root mean square error of 0.89 m. Accuracy is shown to be depth dependent, an
inherent limitation of passive optical detection systems. Accuracy further decreases in areas where turbidity is
likely to be higher, such as locations adjacent to tidal inlets. The SDB maps provide reliable estimations of the
shoreline position and of nearshore isobaths for different cases along the complex coastline analysed. The use
of freely available satellite imagery proved to be a quick and reliable method for acquiring updated mediumresolution,
high-frequency (days and weeks), low-cost bathymetric information for large areas and depths of
up to 12 m in clear waters without wave breaking, allowing almost constant monitoring of the submerged
beach and the shoreface.
Description
Keywords
Satellite-derived bathymetry Ria Formosa Landsat LiDAR Linear transform algorithm Coastal monitoring
Citation
Publisher
Elsevier